MB5370 Module 04. Workshop 2 - Using ggplot2 for communication
Shreyash G Bhandary
2024-05-15
# Load ggplot2 package
library(ggplot2)#Adding a title for your ggplot
ggplot(mpg, aes(displ,hwy)) +
geom_point(aes(colour = class)) +
geom_smooth(se.e = FALSE) +
labs(title = "Fuel efficiency generally decreases with engine size")## Warning in geom_smooth(se.e = FALSE): Ignoring unknown parameters: `se.e`## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
#Adding a sub-title and a caption
ggplot(mpg, aes(displ,hwy)) +
geom_point(aes(colour = class)) +
geom_smooth(se = FALSE) +
labs(
title = "Fuel efficiency generally decreased with engine size",
subtitle = "Two seaters (sports cars) are an exception because of their light weight",
caption = "data from fueleconomy.gov"
)## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
#labs() is used to replace the axis and legend titles
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(colour = class)) +
geom_smooth(se = FALSE) +
labs(
x = "Engine Displacement (L)",
y = "Highway Fuel Economy (mpg)",
colour = "Car Type"
)## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
library(dplyr) # for data manipulation functions##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(magrittr) # for the %>%#Adding annotations in your plot using the geom_text()
best_in_class <- mpg %>%
group_by(class) %>%
filter(row_number(desc(hwy)) == 1)
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(colour = class)) +
geom_text(aes(label = model), data = best_in_class)
##Scales #R automatically adds the scale when you code the ggplot.
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(colour = class))
#Tweaking the scales.
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(colour = class)) +
scale_x_continuous() +
scale_y_continuous() +
scale_colour_discrete()
#Axis Ticks
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
scale_y_continuous(breaks = seq(15, 40, by = 5))
# seq(lower limit, upper limit, by = interval)ggplot(mpg, aes(displ, hwy)) +
geom_point() +
scale_x_continuous(labels = NULL) +
scale_y_continuous(labels = NULL)
#Legends and colour schemes
base <- ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(colour = class))
base + theme(legend.position = "left")
base + theme(legend.position = "top")
base + theme(legend.position = "bottom")
base + theme(legend.position = "right")
#Replacing a scale
ggplot(diamonds, aes(carat, price)) +
geom_bin2d() +
scale_x_log10() +
scale_y_log10()
#Customizing the colour scale for better visualisation.
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(color = drv))
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(color = drv)) +
scale_colour_brewer(palette = "Set1")
#Redundant shape mapping
ggplot(mpg, aes(displ, hwy)) +
geom_point(aes(color = drv, shape = drv)) +
scale_colour_brewer(palette = "Set1")
#Setting a colour palatte of your own using a set of pre-defined colours.
presidential %>%
mutate(id = 33 + row_number()) %>%
ggplot(aes(start, id, colour = party)) +
geom_point() +
geom_segment(aes(xend = end, yend = id)) +
scale_colour_manual(values = c(Republican = "red", Democratic = "blue"))